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Research on Multi-mode Driver Fatigue Detection System

Author: WangMiaoMiao
Tutor: LiuZhenYu
School: Shenyang University of Technology
Course: Signal and Information Processing
Keywords: Face Detection Skin color segmentation The human eye to detect Human mouth detection One-dimensional wavelet transform
CLC: TP274
Type: Master's thesis
Year: 2011
Downloads: 40
Quote: 1
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Abstract


As technology continues to progress , the automotive industry has been rapid development of the world 's total vehicle population has been greatly enhanced . The ensuing traffic accidents also increased year by year , which is also living in no less than the proportion of traffic accidents due to driver fatigue . So has far-reaching significance to the study of this subject . This paper presents a face image processing based visual fatigue detection methods , the use of the camera capture driver to detect the position of the human eye and the mouth and judge its closed state , and then judge whether the driver fatigue . The study in this article is as follows: First, the face image pretreatment , followed by use of non - linear color transform to face the skin detection determined area of the skin color , by determining the size of the area , to exclude non-face skin color region , thereby obtaining the approximate area of the human face . Secondly, on the basis of the positioning access face , for the precise positioning of the human eye and the human mouth . Using the geometric characteristics of the human face , the eyes in the upper half of the face , the combination of gray integral projection and one-dimensional wavelet transform , the precise location of the human eye is obtained in two steps . Obtained after the position of the eyes , the use of the human mouth and the relative position of the human eye , again combined with the gradation integral projection and the one-dimensional wavelet transform algorithm, and obtaining the precise location of the mouth portion . Then, the status determination carried out on the human eye and the human mouth . Light adjustment and threshold segmentation method to extract the characteristics of the human eye and the mouth , by calculating the black pixel value and the height of the plot to determine the state of the eyes and mouth . Finally, the use of the eyes and mouth in a state in the image to determine whether the driver fatigue . When the image display more than five in a row to the human eye closed state judge to fatigue, or more than 10 consecutive images show the human mouth is a yawning state judge for fatigue .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Data processing, data processing system
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